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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.streaming
import java.io.{IOException, ObjectInputStream, ObjectOutputStream}
import scala.collection.mutable.ArrayBuffer
import org.apache.spark.internal.Logging
import org.apache.spark.streaming.dstream.{DStream, InputDStream, ReceiverInputDStream}
import org.apache.spark.streaming.scheduler.Job
import org.apache.spark.util.Utils
final private[streaming] class DStreamGraph extends Serializable with Logging {
private val inputStreams = new ArrayBuffer[InputDStream[_]]()
private val outputStreams = new ArrayBuffer[DStream[_]]()
@volatile private var inputStreamNameAndID: Seq[(String, Int)] = Nil
var rememberDuration: Duration = null
var checkpointInProgress = false
var zeroTime: Time = null
var startTime: Time = null
var batchDuration: Duration = null
@volatile private var numReceivers: Int = 0
def start(time: Time) {
this.synchronized {
require(zeroTime == null, "DStream graph computation already started")
zeroTime = time
startTime = time
outputStreams.foreach(_.initialize(zeroTime))
outputStreams.foreach(_.remember(rememberDuration))
outputStreams.foreach(_.validateAtStart())
numReceivers = inputStreams.count(_.isInstanceOf[ReceiverInputDStream[_]])
inputStreamNameAndID = inputStreams.map(is => (is.name, is.id))
inputStreams.par.foreach(_.start())
}
}
def restart(time: Time) {
this.synchronized { startTime = time }
}
def stop() {
this.synchronized {
inputStreams.par.foreach(_.stop())
}
}
def setContext(ssc: StreamingContext) {
this.synchronized {
outputStreams.foreach(_.setContext(ssc))
}
}
def setBatchDuration(duration: Duration) {
this.synchronized {
require(batchDuration == null,
s"Batch duration already set as $batchDuration. Cannot set it again.")
batchDuration = duration
}
}
def remember(duration: Duration) {
this.synchronized {
require(rememberDuration == null,
s"Remember duration already set as $rememberDuration. Cannot set it again.")
rememberDuration = duration
}
}
def addInputStream(inputStream: InputDStream[_]) {
this.synchronized {
inputStream.setGraph(this)
inputStreams += inputStream
}
}
def addOutputStream(outputStream: DStream[_]) {
this.synchronized {
outputStream.setGraph(this)
outputStreams += outputStream
}
}
def getInputStreams(): Array[InputDStream[_]] = this.synchronized { inputStreams.toArray }
def getOutputStreams(): Array[DStream[_]] = this.synchronized { outputStreams.toArray }
def getReceiverInputStreams(): Array[ReceiverInputDStream[_]] = this.synchronized {
inputStreams.filter(_.isInstanceOf[ReceiverInputDStream[_]])
.map(_.asInstanceOf[ReceiverInputDStream[_]])
.toArray
}
def getNumReceivers: Int = numReceivers
def getInputStreamNameAndID: Seq[(String, Int)] = inputStreamNameAndID
def generateJobs(time: Time): Seq[Job] = {
logDebug("Generating jobs for time " + time)
val jobs = this.synchronized {
outputStreams.flatMap { outputStream =>
val jobOption = outputStream.generateJob(time)
jobOption.foreach(_.setCallSite(outputStream.creationSite))
jobOption
}
}
logDebug("Generated " + jobs.length + " jobs for time " + time)
jobs
}
def clearMetadata(time: Time) {
logDebug("Clearing metadata for time " + time)
this.synchronized {
outputStreams.foreach(_.clearMetadata(time))
}
logDebug("Cleared old metadata for time " + time)
}
def updateCheckpointData(time: Time) {
logInfo("Updating checkpoint data for time " + time)
this.synchronized {
outputStreams.foreach(_.updateCheckpointData(time))
}
logInfo("Updated checkpoint data for time " + time)
}
def clearCheckpointData(time: Time) {
logInfo("Clearing checkpoint data for time " + time)
this.synchronized {
outputStreams.foreach(_.clearCheckpointData(time))
}
logInfo("Cleared checkpoint data for time " + time)
}
def restoreCheckpointData() {
logInfo("Restoring checkpoint data")
this.synchronized {
outputStreams.foreach(_.restoreCheckpointData())
}
logInfo("Restored checkpoint data")
}
def validate() {
this.synchronized {
require(batchDuration != null, "Batch duration has not been set")
// assert(batchDuration >= Milliseconds(100), "Batch duration of " + batchDuration +
// " is very low")
require(getOutputStreams().nonEmpty, "No output operations registered, so nothing to execute")
}
}
/**
* Get the maximum remember duration across all the input streams. This is a conservative but
* safe remember duration which can be used to perform cleanup operations.
*/
def getMaxInputStreamRememberDuration(): Duration = {
// If an InputDStream is not used, its `rememberDuration` will be null and we can ignore them
inputStreams.map(_.rememberDuration).filter(_ != null).maxBy(_.milliseconds)
}
@throws(classOf[IOException])
private def writeObject(oos: ObjectOutputStream): Unit = Utils.tryOrIOException {
logDebug("DStreamGraph.writeObject used")
this.synchronized {
checkpointInProgress = true
logDebug("Enabled checkpoint mode")
oos.defaultWriteObject()
checkpointInProgress = false
logDebug("Disabled checkpoint mode")
}
}
@throws(classOf[IOException])
private def readObject(ois: ObjectInputStream): Unit = Utils.tryOrIOException {
logDebug("DStreamGraph.readObject used")
this.synchronized {
checkpointInProgress = true
ois.defaultReadObject()
checkpointInProgress = false
}
}
}
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